Skip to main content
SpringerLink
Log in
Book cover

Ridges in Image and Data Analysis

  • Book
  • © 1996

Overview

Authors:
  1. David Eberly

    1. SAS Institute, Inc., Cary, USA

    View author publications

    You can also search for this author in PubMed   Google Scholar

Part of the book series: Computational Imaging and Vision (CIVI, volume 7)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (7 chapters)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. Introduction

    • David Eberly
    Pages 1-7

  3. Mathematical Preliminaries

    • David Eberly
    Pages 9-38

  4. Ridges in Euclidean Geometry

    • David Eberly
    Pages 39-63

  5. Ridges in Riemannian Geometry

    • David Eberly
    Pages 65-73

  6. Ridges of Functions Defined on Manifolds

    • David Eberly
    Pages 75-95

  7. Applications to Image and Data Analysis

    • David Eberly
    Pages 97-154

  8. Implementation Issues

    • David Eberly
    Pages 155-201

  9. Back Matter

    Pages 203-215
    Download chapter PDF
Back to top

Keywords

About this book

The concept of ridges has appeared numerous times in the image processing liter­ ature. Sometimes the term is used in an intuitive sense. Other times a concrete definition is provided. In almost all cases the concept is used for very specific ap­ plications. When analyzing images or data sets, it is very natural for a scientist to measure critical behavior by considering maxima or minima of the data. These critical points are relatively easy to compute. Numerical packages always provide support for root finding or optimization, whether it be through bisection, Newton's method, conjugate gradient method, or other standard methods. It has not been natural for scientists to consider critical behavior in a higher-order sense. The con­ cept of ridge as a manifold of critical points is a natural extension of the concept of local maximum as an isolated critical point. However, almost no attention has been given to formalizing the concept. There is a need for a formal development. There is a need for understanding the computation issues that arise in the imple­ mentations. The purpose of this book is to address both needs by providing a formal mathematical foundation and a computational framework for ridges. The intended audience for this book includes anyone interested in exploring the use­ fulness of ridges in data analysis.

Authors and Affiliations

  • SAS Institute, Inc., Cary, USA

    David Eberly

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation